Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net

Jiyang Dong; Qianwen Peng; Lingli Deng; Chao Zhao; Zongwei Cai

doi:10.1016/j.xpro.2023.102159

Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net

STAR Protoc. 2023 Mar 13;4(2):102159. doi: 10.1016/j.xpro.2023.102159. Online ahead of print.

Authors

Jiyang Dong¹, Qianwen Peng¹, Lingli Deng², Chao Zhao³, Zongwei Cai⁴

Affiliations

¹ Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China.
² Department of Information Engineering, East China University of Technology, Nanchang 33000, China.
³ Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China; Shenzhen Key Laboratory of Precision Diagnosis and Treatment of Depression, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China. Electronic address: chao.zhao@siat.ac.cn.
⁴ State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR 999077, China. Electronic address: zwcai@hkbu.edu.hk.

Abstract

Biomolecule regulation and communication between cells and organs show specific network and regional features and play an important role in disease progression. Here, we describe steps for in situ detection of biomolecules with detailed spatial distribution using imaging mass spectrometry (iMS). Using the information on inter-cells and inter-organs metabolic interactions provided by iMS, we detail the establishment of an iMS-dataset-sourced multiscale network strategy and present steps for exploring metabolic responses in environmental-exposure-induced disease model. For complete details on the use and execution of this protocol, please refer to Dong et al. (2022).¹.

Keywords: Bioinformatics; Biotechnology and bioengineering; Computer sciences; Environmental sciences; Metabolism.